Citation

Wang J, Li Y, Liu J, He K, Wang P. PLoS One 2013; 8(11): e80178.

Affiliation

School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, P.R. China.

Copyright

(Copyright © 2013, Public Library of Science)

DOI

10.1371/journal.pone.0080178

PMID

24260355

PMCID

PMC3832441

Abstract

Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.

Language: en